For use in collecting data on roads and road surfaces, there are currently no automated methods that permit large-scale material characterization in the field. Skid resistance is usually determined through contact methods based on friction, which is poorly suited for high-speed or large-scale data collection. Ground radar methods require bulky hardware and extensive mechanical support; they also provide excess data which are not necessary for a quick estimation or verification of surface conditions. Optical techniques are limited to surface features and require substantial processing; they also are expensive because of the large amount of data collected. Optical methods can yield false positives because of artifacts and features that are often misidentified by the imaging algorithms employed. Thus, there remains a need for data collection apparatus and methods that are suitable for high-speed and large-scale data collection of road condition, road surface features, and road subsurface characteristics.